Sahas Induwara
ZUU-AIEE-5eae6455-6796-4a41-acd2-029d14e7a252
September 11, 2026
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SI

Issued to

Sahas Induwara

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Credential Verification

Issue date: September 11, 2026

ID: 5eae6455-6796-4a41-acd2-029d14e7a252

Issued by

Zuu Crew AI

Type

Course

Level

Advanced

Format

Online

Duration

14 weeks

Price

Paid

Description

Awarded to learners who complete ZuuCrew AI's 14-week AI Engineer Essentials track, designing, building and deploying production-grade agentic LLM systems, progressing from prompt engineering and parameter-efficient fine-tuning through advanced and corrective retrieval, context engineering, multi-tier agent memory, LangGraph multi-agent orchestration, knowledge-graph RAG, MCP tool integration, and a deployed voice-enabled agent swarm running on AWS.

Skills

Large Language Models (LLM)

Prompt Engineering

Retrieval-Augmented Generation (RAG)

LangChain

Multi-Agent Systems

Fine-Tuning (LoRA/QLoRA)

Vector Databases

Knowledge Graphs

Model Context Protocol (MCP)

LLM Observability

Voice AI

Docker

Amazon Web Services (AWS)

Python (Programming Language)

Earning Criteria

Participation

Complete all 14 weekly modules

Assignment

Complete the five mini projects (prompt-engineered crisis intelligence pipeline, a fine-tuning versus hybrid-RAG evaluation showdown, a context-engineering platform with CAG and corrective RAG, a memory-driven agentic concierge with reflection, and a multi-agent natural-language-to-SQL analytics system)

Assignment

Complete the final hackathon capstone delivering an incident-resolution agent swarm with MCP servers, four-tier memory, LiveKit voice escalation, Langfuse observability and AWS deployment.

Assignment

Demonstrate the ability to engineer reliable LLM pipelines, orchestrate multi-agent workflows with structured state, ground responses in retrieved evidence, and operate deployed systems under cost and safety guardrails.